Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
FollowEval: A Multi-Dimensional Benchmark for Assessing the Instruction-Following Capability of Large Language Models
As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2311.09829.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-12T19:21:59.082243Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-13T01:47:04.050716Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation b707f8a9-0b69-4068-9772-b0a142164054 · inbound
LCTG Bench: LLM Controlled Text Generation Benchmark cites this paper.
LCTG Bench: LLM Controlled Text Generation Benchmark FollowEval: A Multi-Dimensional Benchmark for Assessing the Instruction-Following Capability of Large Language Models
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T13:53:45.047113Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 80cd3bb1-90be-4ef7-bb44-8c12aa87e8be · inbound
TReB: A Comprehensive Benchmark for Evaluating Table Reasoning Capabilities of Large Language Models cites this paper.
TReB: A Comprehensive Benchmark for Evaluating Table Reasoning Capabilities of Large Language Models FollowEval: A Multi-Dimensional Benchmark for Assessing the Instruction-Following Capability of Large Language Models
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T23:20:02.097569Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 01b32f49-366c-49ab-8178-7a476c009360 · inbound
How Many Instructions Can LLMs Follow at Once? cites this paper.
How Many Instructions Can LLMs Follow at Once? FollowEval: A Multi-Dimensional Benchmark for Assessing the Instruction-Following Capability of Large Language Models
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T17:13:47.227859Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3ccc14a2-14db-4e67-8759-426f51fc79a4 · inbound
Inverse IFEval: Can LLMs Unlearn Stubborn Training Conventions to Follow Real Instructions? cites this paper.
Inverse IFEval: Can LLMs Unlearn Stubborn Training Conventions to Follow Real Instructions? FollowEval: A Multi-Dimensional Benchmark for Assessing the Instruction-Following Capability of Large Language Models
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T10:16:51.156699Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6f08d9cb-51ea-4058-b4a9-d3b13a98c906 · inbound
ReAD: Reinforcement-Guided Capability Distillation for Large Language Models cites this paper.
ReAD: Reinforcement-Guided Capability Distillation for Large Language Models FollowEval: A Multi-Dimensional Benchmark for Assessing the Instruction-Following Capability of Large Language Models
Reference 15
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T01:47:04.053427Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation e1fda741-9ab2-465b-8824-813dcb2ae246 · inbound
SPIEval: Evaluating Large Language Models as Mobile Assistants over Scattered Personal Information cites this paper.
SPIEval: Evaluating Large Language Models as Mobile Assistants over Scattered Personal Information FollowEval: A Multi-Dimensional Benchmark for Assessing the Instruction-Following Capability of Large Language Models
Reference 75
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T19:21:59.082243Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.